Large-scale evaluation of text features affecting perceived and actual text diffi

影响感知和实际文本差异的文本特征的大规模评估

• 批准号: 8240419
• 负责人: GONDY LEROY
• 金额: $ 3.35万
• 依托单位: CLAREMONT GRADUATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-03-15 至 2013-07-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8240419
• 关键词: Address; Affect; Caring; Chronic Disease; Computer-Assisted Image Analysis; Controlled Environment; Data; Data Set; Development; Diagnosis; Educational Materials; Ensure; Environment; Evaluation; Future; Goals; Guidelines; Health; Health Care Costs; Imagery; Information Sciences; Knowledge; Laboratory Study; Lead; Learning; Life; Linguistics; Marketing; Measures; Mechanics; Medical; Medical Informatics; Participant; Patients; Physicians; Process; Publishing; Readability; Reading; Research; Research Personnel; Resources; Sampling; Schools; Semantics; Societies; Students; Technology; Testing; Text; Time; Translating; Work; Writing; base; cost; cost effective; cost efficient; density; design; health literacy; insight; pressure; programs; public health relevance; skills; spelling; tool; virtual

DESCRIPTION (provided by applicant): With increasingly more medical tests and treatments being available, more patients being diagnosed with chronic diseases that require life-long management, and increasing pressure on clinicians to see more patients in a limited amount of time, it is essential that patients learn and understand how best to take care of their health. Unfortunately, an estimated 89 million people have insufficient health literacy to do just that and the associated costs are estimated to be into the billions of dollars each year. Although there are many exciting opportunities to educate consumers, ranging from visualization to virtual environments, text is still the most efficient and cost-effective medium available to all groups in society. Unfortunately, existing writing guidelines, relying heavily on readability formulas, have not been shown to impact text difficulty or consumer understanding. Objectives The objectives of this project are therefore to address and overcome existing barriers in current readability research. We address barriers as follows: we will work 1) with representative consumers, not experts evaluating on behalf of consumers, 2) using a large sample with thousands of participants working in their own settings, not a laboratory study with few participants in an artificial environment, and 3) evaluate both perceived and actual difficulty of text, two variables often confounded in studies, 4) to discover features that can be automatically discovered in text so that difficulty checkers can be developed that allow clinicians to efficiently and effectively optimize their text without requiring study of guidelines or linguistics. Design The study will be conducted using modern technology and resources. Over a time period of two years, master and doctoral level students will design and conduct the studies together with the principle investigator. The study brings together insights from computational linguistics and information science applied to medical informatics. Starting from a linguistic perspective, we will we systematically list good candidates of text features that may influence understanding. We will look at features of grammar, semantics, and compositions of text. By using a modern market place, Amazon's Mechanical Turk, we can involve thousands of participants in the study. We will each pair-wise comparisons of the features, e.g., sentences with high versus low topic density. Using a within-subjects design, we will measure perceived and actual difficulty of each feature with multiple choice question-answering tasks. PUBLIC HEALTH RELEVANCE: Current health information is not attuned to the reading skills of consumers a situation that contributes to low health literacy and higher healthcare costs because of costly mistakes and unwise decisions. The proposed project will work with thousands of representative consumers to discover text features that influence perceived and actual difficulty of text. These features will lead to better writing guidelines and automated tools to help clinicians write health educational materials that are easier to understand and that are based on demonstrated impacts of the features on understanding.

描述（由申请人提供）：随着越来越多的医学检查和治疗，更多的患者被诊断出患有需要终身管理的慢性疾病，以及临床医生在有限的时间内看到更多患者的压力增加，这是必不可少的患者学习并了解如何最好地照顾自己的健康。不幸的是，估计有8900万人的健康素养不足以做到这一点，并且相关费用估计每年是数十亿美元。尽管有许多令人兴奋的机会来教育消费者，从可视化到虚拟环境，但文本仍然是社会所有群体可用的最有效，最具成本效益的媒介。不幸的是，现有的写作指南严重依赖可读性公式，并未被证明会影响文本困难或消费者的理解。因此，该项目的目标旨在解决并克服当前可读性研究中的现有障碍。我们将解决以下障碍：我们将与代表性消费者一起工作1），而不是代表消费者评估的专家，2）使用大型样本，成千上万的参与者在自己的环境中工作，而不是在人工环境中与少数参与者进行实验室研究，和3）评估文本的感知和实际难度，研究经常混淆，4）发现可以在文本中自动发现的功能，以便可以开发出困难的检查器，从而允许临床医生在没有的情况下有效地优化其文本需要研究准则或语言学。设计研究将使用现代技术和资源进行。在两年的时间内，硕士和博士学位学生将与主要研究人员一起设计和进行研究。这项研究汇集了应用于医学信息学的计算语言学和信息科学的见解。 从语言角度开始，我们将系统地列出可能影响理解的文本特征的良好候选者。我们将研究语法，语义和文本组成的特征。通过使用现代市场，亚马逊的机械土耳其人，我们可以参与研究。我们将对功能的每个配对比较，例如具有高主题密度与低主题密度的句子。使用受试者内部设计，我们将通过多项选择提问任务来衡量每个功能的感知和实际难度。 公共卫生相关性：由于昂贵的错误和不明智的决定，当前的健康信息不适合消费者的阅读技能，这种情况会导致健康素养和更高的医疗保健费用。拟议的项目将与成千上万的代表消费者合作，发现影响感知和实际困难的文本功能。这些功能将带来更好的编写指南和自动化工具，以帮助临床医生编写易于理解的健康教育材料，并且基于这些特征对理解的影响。